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Trajectories of maternal depression: a 27-year population-based prospective study

Published online by Cambridge University Press:  19 January 2016

J. M. Najman ,
M. Plotnikova ,
G. M. Williams ,
R. Alati ,
A. A. Mamun ,
J. Scott ,
N. Wray  and
A. M. Clavarino
J. M. Najman*
Affiliation:
Schools of Public Health and Social Science, The University of Queensland, Brisbane, Australia
M. Plotnikova
Affiliation:
School of Public Health, The University of Queensland, Brisbane, Australia
G. M. Williams
Affiliation:
School of Public Health, The University of Queensland, Brisbane, Australia
R. Alati
Affiliation:
School of Public Health, The University of Queensland, Brisbane, Australia
A. A. Mamun
Affiliation:
School of Public Health, The University of Queensland, Brisbane, Australia
J. Scott
Affiliation:
UQCCR, The University of Queensland, Brisbane, Australia
N. Wray
Affiliation:
Queensland Brain Institute, The University of Queensland, Brisbane, Australia
A. M. Clavarino
Affiliation:
School of Pharmacy, The University of Queensland, Brisbane, Australia
*
*Address for correspondence: J. M. Najman, Ph.D.FASSA, School of Public Health, School of Social Science, The University of Queensland, Herston Road, Herston, QLD 4006, Australia. (Email: j.najman@uq.edu.au)
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Abstract

Aims.

To identify distinct trajectories of depression experienced by a population-based sample of women over a 27-year period and to assess the validity of the derived trajectories.

Method.

The Mater University of Queensland Study of Pregnancy is a birth cohort study which commenced in 1981. Women (N = 6753) were interviewed at their first clinic visit, at 6 months, then 5, 14, 21 and 27 years after the birth of their child, using the Delusions Symptoms – States Inventory. Some 3561 (52.7%) women were followed up at 27 years, with 3337 (49.4%) of the sample completing the Composite International Diagnostic Interview (CIDI). Depression trajectories over a 27-year period were identified using Latent Class Growth Modelling (LCGM). LCGM was used to identify respondents with similar patterns of depression over a 27-year period. At the 27-year follow-up women who completed the CIDI, were stratified according to their trajectory group membership.

Results.

Three trajectory groups, each with different life-course patterns of depression were identified. The low/no symptoms of depression trajectory group comprised 48.4% of women. The mid-depression group (41.7%) had a consistent pattern of occasional symptoms of depression. The high/escalating trajectory group comprised 9.9% of the women in the study. We then examined each trajectory group based on their completion of the CIDI at the 27-year follow-up. Using the CIDI, 27.0% of women in the study had met the DSM-IV criteria for lifetime ever depression by their mean age of 46.5 years. The responses to the CIDI differed greatly for each of the trajectory groups, suggesting that the trajectories validly reflect different life histories of depression. The high/escalating trajectory group had an earlier age of first onset, more frequent episodes, longer duration of each episode of depression and experienced higher levels of impairment for their episodes of depression. For the high symptoms trajectory group, clinically significant depression is estimated to be experienced by women almost one in every 6 days of their life.

Conclusion.

While symptoms of depression are commonly experienced in a large community-based sample of women, a minority of women experience many episodes of depression in their lifetime. It is this group of women who are most impaired and should be of most concern, and who should be the main target of prevention and treatment initiatives.

Keywords

Depressionpopulation surveyprospective studywomen
Type
Original Articles
Information
Epidemiology and Psychiatric Sciences , Volume 26 , Issue 1 , February 2017 , pp. 79 - 88
Copyright
Copyright © Cambridge University Press 2016 

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References

Andrade, L, Caraveo-Anduaga, JJ, Berglund, P, Bijl, RV, De Graaf, R, Vollebergh, W, Dragomirecka, E, Kohn, R, Keller, M, Kessler, RC, Kawakami, N, Kilic, C, Offord, D, Ustun, TB, Vicente, B, Wittchen, HU (2003). The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) Surveys. International Journal of Methods in Psychiatric Research 12, 3–21.CrossRefGoogle Scholar
Andrews, G, Poulton, R, Skoog, I (2005). Lifetime risk of depression: restricted to a minority or waiting for most? British Journal of Psychiatry 187, 495–496.CrossRefGoogle ScholarPubMed
Angst, J, Paksarian, D, Cui, L, Merikangas, KR, Hengartner, MP, Ajdacic-Gross, V, Rössler, W (2015). The epidemiology of common mental disorders from age 20 to 50: results from the prospective Zurich cohort Study. Epidemiology and Psychiatric Sciences, 1–9.Google ScholarPubMed
Arbuckle, R, Frye, MA, Brecher, M, Paulsson, B, Rajagopalan, K, Palmer, S, Degl'Innocenti, A (2009). The psychometric validation of the Sheehan Disability Scale (SDS) in patients with bipolar disorder. Psychiatry Research 165, 163–174.Google Scholar
Beard, JR, Galea, S, Vlahov, D (2008). Longitudinal population-based studies of affective disorders: where to from here? BMC Psychiatry 8, 83.Google Scholar
Bedford, A, Foulds, GA (1977). Validation of the delusions symptoms states inventory. British Journal of Medical Psychology 50, 163–171.CrossRefGoogle Scholar
Bedford, A, Foulds, GA, Sheffield, BF (1976). A new personal disturbance scale (DSSI/sAD). British Journal of Social and Clinical Psychology 15, 387–394.CrossRefGoogle ScholarPubMed
Belsky, J, Hartman, S (2014). Gene-environment interaction in evolutionary perspective: differential susceptibility to environmental influences. World Psychiatry 13, 87–89.CrossRefGoogle ScholarPubMed
Biesheuvel-Leliefeld, KEM, Hollon, SD, van Marwijk, HWJ, Cuijpers, P, Bockting, CLH, Kok, GD, Smit, F (2015). Effectiveness of phsychological interventions in preventing recurrence of depressive disorder: meta- anlysis and meta-regression. Journal of Affective Disorders 174, 400–410.Google Scholar
Caspi, A, Sugden, K, Moffitt, TE, Taylor, A, Craig, IW, Harrington, H, McClay, J, Mill, J, Martin, J, Braithwaite, A, Poulton, R (2003). Influence of life stress on depression: moderation by a polymorphism in the 5-HTT Gene. Science 301, 386–389.Google Scholar
Heim, C, Binder, EB (2012). Current research trends in early life stress and depression: review of human studies on sensitive periods, gene–environment interactions, and epigenetics. Experimental Neurology 233, 102–111.CrossRefGoogle ScholarPubMed
Jones, BL, Nagin, DS, Roeder, K (2001). A SAS procedure based on mixture models for estimating developmental trajectories. Sociological Methods and Research 29, 374–393.CrossRefGoogle Scholar
Kessler, RC, Ustun, TB (2004). The world mental health (WMH) survey initiative version of the world health organization (WHO) composite international diagnostic interview (CIDI). International Journal of Methods in Psychiatric Research 13, 93–121.CrossRefGoogle ScholarPubMed
Kessler, RC, Wang, PS (2009). Epidemiology of depression. In Handbook of Depression (ed. Gotlib, IH and Hammen, CL), pp. 5–22. Guilford Press: New York.Google Scholar
Kessler, RC, Kendler, KS, Wittchen, HU, Hughes, M, Eshleman, S, Zhao, S, McGonagle, KA, Nelson, CB (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Archives of General Psychiatry 51, 8–9.Google Scholar
Kessler, RC, Walters, EE, Rush, AJ, Demler, O, Merikangas, KR, Jin, R, Wang, PS, Berglund, P, Koretz, D (2003). The epidemiology of major depressive disorder. Journal of the American Medical Association 289, 3095–3105.CrossRefGoogle ScholarPubMed
Kruijshaar, ME, Barendregt, J, Vos, T, De Graff, R, Spijker, J, Andrews, G (2005). Lifetime prevalence estimates of major depression: an indirect estimation method and a quantification of recall bias. European Journal of Epidemiology 20, 103–111.Google Scholar
Luoma, I, Korhonen, M, Salmelin, RK, Helminen, M, Tamminen, T (2015). Long-term trajectories of maternal depressive symptoms and their antenatal predictors. Journal of Affective Disorders 170, 30–38.CrossRefGoogle ScholarPubMed
Lynch, K, Roeder, K, Nagin, D (1999). Modeling uncertainty in latent class membership: a case study in criminology. Journal of the American Statistical Association 94, 766–776.Google Scholar
Moffitt, TE, Caspi, A, Taylor, A, Kokaua, J, Milne, BJ, Polanczyk, G, Poulton, R (2010). How common are the common mental disorders? Psychological Medicine 40, 899–909.Google Scholar
Mueller, TI, Leon, AC, Keller, MB, Solomon, DA, Endicott, J, Coryell, W, Warshaw, M, Maser, JD (1999). Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. American Journal of Psychiatry 156, 1000–1006.CrossRefGoogle ScholarPubMed
Nagin, D (1999). Analyzing developmental trajectories: a semiparametric, group-based approach. Psychological Methods 4, 139–157.CrossRefGoogle Scholar
Nagin, D (2005). Group-based Modeling of Development. Harvard University Press: Cambridge.Google Scholar
Nagin, D, Tremblay, RS (2005). Developmental trajectory groups: fact or a useful statistical fiction? Criminology 43, 873–918.CrossRefGoogle Scholar
Najman, JM, Anderson, MJ, Bor, W, O'Callaghan, MJ, Williams, GM (2000). Postnatal depression – myth and reality: maternal depression before and after the birth of a child. Social Psychiatry and Psychiatric Epidemiology 35, 19–27.Google Scholar
Najman, JM, Bor, W, O'Callaghan, M, Williams, GM, Aird, R, Shuttlewood, G (2005). Cohort profile: the Mater-University of Queensland Study of Pregnancy (MUSP). International Journal of Epidemiology 34, 992–997.Google Scholar
Najman, JM, Khatun, M, Mamun, A, Clavarino, A, Williams, GM, Scott, J, O'Callaghan, M, Hayatbakhsh, R, Alati, R (2014). Does depression experienced by mothers lead to a decline in marital quality: a 21-year longitudinal study. Social Psychiatry and Psychiatric Epidemiology 49, 121–132.CrossRefGoogle ScholarPubMed
Nandi, A, Beard, JR, Galea, S (2009). Epidemiologic heterogeneity of common mood and anxiety disorders over the lifecourse in the general population: a systematic review. BMC Psychiatry 9, 31–31.CrossRefGoogle ScholarPubMed
Sheehan, DV, Harnett-Sheehan, K, Raj, BA (1996). The measurement of disability. International Clinical Psychopharmacology 11, 89–95.CrossRefGoogle ScholarPubMed
Solomon, DA, Keller, MB, Leon, AC, Mueller, TI, Lavori, PW, Shea, MT, Coryell, W, Warshaw, M, Turvey, C, Maser, JD, Endicott, J (2000). Multiple recurrences of major depressive disorder. American Journal of Psychiatry 157, 229–233.Google Scholar
Stoolmiller, M, Kim, HK, Capaldi, DM (2005). The course of depressive symptoms in men from early adolescence to young adulthood: identifying latent trajectories and early predictors. Journal of Abnormal Psychology 114, 331–345.CrossRefGoogle ScholarPubMed
Sutin, AR, Terracciano, A, Milaneschi, U, An, Y, Ferrucci, L, Zonderman, AB (2013). The trajectory of depressive symptoms across the adult life span. Journal of the American Medical Association Psychiatry 70, 803.Google Scholar
Vos, T, Haby, MM, Barendregt, JJ, Kruijshaar, M, Corry, J, Andrews, G (2004). The burden of major depression avoidable by longer-term treatment strategies. Archives of General Psychiatry 61, 1097–1103.CrossRefGoogle ScholarPubMed
Whiteford, HA, Harris, MG, McKeon, G, Baxter, A, Pennell, C, Barendregt, JJ, Wang, J (2013). Estimating remission from untreated major depression: a systematic review and meta-analysis. Psychological Medicine 43, 1569–1585.CrossRefGoogle ScholarPubMed
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